Getting started with using mechanistic modeling to guide portfolio decisions
How do you know if a drug will work, before you even make the molecule?
At the earliest stages of discovery, teams must make critical decisions about targets, modalities, and design strategies with limited data. Mechanistic modeling offers a powerful way to evaluate feasibility, define optimal drug properties, and prioritize the most promising paths forward — before significant resources are committed.
Watch Certara experts Marc Presler, PhD, and Sarah DiBartolo, as they answer real audience questions in this Q&A-style session on applying early-stage biosimulation to biologics discovery. Get direct access to expert insight on how modeling can support faster, more confident portfolio decisions early in drug discovery.
What you’ll learn:
- What “early feasibility” means and why it matters in biologics discovery
- How mechanistic modeling can inform target selection and candidate prioritization
- How to define optimal drug properties (e.g., affinity, half-life, valency) before molecule generation
- What inputs and data are needed to get started with early-stage modeling
- How to apply biosimulation to triage non-viable concepts and focus resources
演讲嘉宾：
Marc Presler, PhD — Director, QSP, Certara
Sarah DiBartolo — Associate Principal Scientist, QSP, Certara
